Signal dysfunction, also known as outlier, anomaly, novelty or event detection, represents one of the most challenging subjects in real time data mining due to the difficulties in achieving computational efficiency, causality, and minimum information drift (i.e., time shifting). In the particular case of real time well drilling operation, it is critical to develop mechanisms that are capable of detecting dysfunctions that would eventually lead to costly drill system failures.